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Ingest, search, and retain autonomous agent logs with pay-per-line billing.
This MCP tool is described as an open-source log ingestion service supporting paid NDJSON log posting and log search/tailing; no required secrets or declared remote endpoints are provided, but its logging and local execution properties still warrant attention. No clear high-risk red flags are evident from the materials, with the main concerns being incomplete documentation, weak community validation, and potential exposure of log data.
The materials explicitly state that no keys or environment variables are required, and there is no factual indication that users must provide API keys, wallet private keys, or other sensitive secrets. However, the phrase 'USDC payment per line' implies a payment mechanism, and the missing documentation leaves the actual credential handling unclear.
The tool is described as a 'log ingestion server,' so its core function inherently involves receiving and serving log data. Although the metadata says there are no remote endpoints, the description references Base L2 payment usage, which suggests possible network interaction. The materials do not specify hosts, data flows, or whether logs are sent to third parties, so caution is warranted.
The system flags this tool as executes-code, meaning it runs a local service or related code on the host. This inherent capability alone does not justify a high-risk rating, but the materials do not describe process privilege boundaries, whether it invokes blockchain/system commands, or whether it listens on local ports.
The description says it can post, tail, and search logs, indicating that it processes and retains agent log data, with configurable retention tiers. The materials do not specify storage location, access controls, or how 'own logs' isolation is enforced, leaving the scope of local or server-side log access insufficiently transparent.
Positive factors include being open source under the MIT license and therefore auditable, which materially lowers the risk. Points to watch are that it comes from a third-party registry, has 0 GitHub stars, unknown maintenance status, and no README, which weakens confidence in maturity and ongoing upkeep.
Copy the install command and let the AI configure it · recommended for beginners
No copy-paste install info for "hive-mcp-log" yet — see the docs or source repo.
Convert the following agent runtime events into NDJSON logs and explain how to send them to hive-mcp-log: task started, tool called, result returned, task finished. Each line should include timestamp, agent_id, event, and message.
Provides ready-to-post NDJSON log examples plus guidance for ingestion and field design.
Help me design a log search request to find all logs for agent_id alpha-7 from the last 24 hours containing error, timeout, or retry, returned in reverse chronological order.
Returns clear search criteria, example queries, and result fields for faster troubleshooting.
Create a log retention plan for hive-mcp-log with these requirements: debug logs kept for 3 days, audit logs for 90 days, critical error logs retained long term, while controlling costs.
Outputs tiered retention recommendations, suitable log types, and cost-versus-observability tradeoffs.
Get parametric insurance for autonomous agents against uptime, slippage, and oracle failures.
Keep verifiable, tamper-evident audit logs of AI agent actions.
Tail, search, filter, and summarize logs from files and Docker containers.
Create tamper-evident signed audit logs for agent calls, handoffs, and decisions
Monitor GCP Java microservice logs and investigate issues with natural-language queries.
Query Everlog diary exports for reflection, evidence retrieval, and self-model maintenance.